2 citations · 2 across the 1 of their papers we have counts for
3 papers
cs.CL2024★ 2 cited
An Empirical Study on Information Extraction using Large Language Models
Ridong Han, Chaohao Yang, Tao Peng +4
Human-like large language models (LLMs), especially the most powerful and popular ones in OpenAI's GPT family, have proven to be very helpful for many natural language processing (…
cs.CL2023
An Empirical Study on Information Extraction using Large Language Models
Ridong Han, Chaohao Yang, Tao Peng +4
Human-like large language models (LLMs), especially the most powerful and popular ones in OpenAI's GPT family, have proven to be very helpful for many natural language processing (…
cs.CL2022
Document-level Relation Extraction with Relation Correlations
Ridong Han, Tao Peng, Benyou Wang +2
Document-level relation extraction faces two overlooked challenges: long-tail problem and multi-label problem. Previous work focuses mainly on obtaining better contextual represent…